A hierarchical hub location model for the integrated design of urban and rural logistics networks under demand uncertainty

Li, Zhichun; Xue, Bing; Fu, Xiaowen

doi:10.1007/s10479-023-05189-6

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…In the aspects of traffic network design and optimization, it includes the traffic equilibrium model [16], bus route optimization [17], multimodal transportation route optimization [18], and hub-and-spoke airline network design [19]. In addition, much logistics network research has considered the demand uncertainty, such as the location of urban-rural logistics integration design [20], urban subway underground logistics system layout problem [21], and multimodal logistics network design problem [22].…”

Section: Introductionmentioning

confidence: 99%

An Assessment Scheme for Road Network Capacity under Demand Uncertainty

Zhou

et al. 2023

Applied Sciences

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Network capacity is a vital index with which to assess the operation of traffic networks. The majority of existing traffic network capacity models are formed as bi-level programming, which maximizes the traffic flows under equilibrium constraints and is extremely dependent on the current origin–destination (O–D) travel demand. However, an accurate O–D matrix is not easy to obtain in practice. This article aims to provide an assessment method for traffic network capacity under demand uncertainty. To consider the variation in real demand in traffic networks, the current travel demand is treated as unknown parameters that are defined inside a restricted set. Based on the hypothesis of different probability distributions, the road network capacity is calculated by repeated capacity loading experiments with a random sampling of uncertain parameters. To improve the efficiency of the repeated calculations of the traffic assignment model, a sensitivity-analysis-based (SAB) approximation method was developed to avoid the double calculation of the network capacity model for each random O–D matrix. The SAB method significantly improved the calculation efficiency while ensuring accuracy. Using simulation experiments, we researched the reliability of road network capacity and the probabilities of high congestion for each link under uncertain demand.

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Section: Introductionmentioning

confidence: 99%

An Assessment Scheme for Road Network Capacity under Demand Uncertainty

Zhou

et al. 2023

Applied Sciences

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“…Limited research has been conducted on hybrid network-based path analysis algorithms. Some have proposed hierarchical hub location models, treating hub locations as transfer stations, and conducting optimal path analysis by searching the paths from ordinary station to transfer station and vice versa [33][34][35]. However, these algorithms often use the number of transfers as the primary evaluation criterion, and neglect factors like the distance, time, and cost.…”

Section: Introductionmentioning

confidence: 99%

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

Feng,

Zhang,

Zhu

2023

Applied Sciences

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The modern urban transportation service network could be split into unrestricted and restricted networks depending on whether travelers face limitations in route selection. Along with the continuous expansion of the city, it is difficult for travelers to find a more reasonable travel solution when confronted with such a complex transportation service network, which combines both unrestricted and restricted networks, especially for the park-and-ride (P&R) travel mode. This paper addresses the issue of route analysis in modern urban transportation service systems to provide travelers with reasonable travel solutions based on multiple types of transportation services. An improved A* algorithm is proposed to address the optimal path analysis for restricted networks to provide reasonable travel solutions for public transportation trips. Furthermore, by establishing the topological relationship between restricted and unrestricted networks, this paper presented an improved A* algorithm based on hybrid networks that solves the optimal path analysis problem for P&R trips, bringing convenience to many urban travelers.

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“…Some research projects have been completed, though, regarding uncertainty [16][17][18][19][20][21][22][23][24][25][26][27][28]. Numerous research studies have been conducted on solution techniques to date [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46]. {Please insert Table 1 about here.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective three-level hierarchical hub location-queue problem with congestion and reliability under uncertainty: A case study

Yahyapour-Ganji,

Ghodratnama,

Tavakkoli-Moghaddam

2023

Scientia Iranica

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This study investigates a three-level hierarchical hub problem considering numerous features, such as congestion and reliability. This relates to ground and air hubs as high layers in this hierarchical network. A four-objective model is presented; it lowers the number of routes, network-related costs, and hub queue waiting times while raising the network's route reliability. Due to the impact of service time on customer satisfaction in this issue, a time frame that a penalty is assigned for the amount of delay is considered. Both the airport and the ground are hub facilities in this regard. M/M/C/K queue systems are those found in the airport and ground hubs. Due to the multi-objective nature of the problem, the LP-metric and goal attainment (GA) approaches are used to resolve it and verify multiple samples with varying weight values provided by the decision-maker. The results from the above-mentioned methods are ranked using a simple additive weighting (SAW) method. A few parameters are treated as fuzzy numbers to make the model more realistic, and the Jimenez's model and chance-constrained programming are used to present the findings. Considering numerous weights for each objective function and solving two methods, Pareto solutions are obtained.

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A hierarchical hub location model for the integrated design of urban and rural logistics networks under demand uncertainty

Cited by 5 publications

References 43 publications

An Assessment Scheme for Road Network Capacity under Demand Uncertainty

An Assessment Scheme for Road Network Capacity under Demand Uncertainty

Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

A multi-objective three-level hierarchical hub location-queue problem with congestion and reliability under uncertainty: A case study

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